In your coverage, please use this URL to provide access to the freely available article in PLOS Digital Health: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000088
Credit: Juneau P, et al., 2022, PLOS Digital Health, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
In your coverage, please use this URL to provide access to the freely available article in PLOS Digital Health: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000088
Article Title: Automated step detection with 6-minute walk test smartphone sensors signals for fall risk classification in lower limb amputees
Author Countries: Canada, Slovenia
Funding: This research was funded by Natural Sciences and Engineering Research Council of Canada (NSERC). NSERC CREATE READI: RGPIN-2019-04106, E. D. L., https://carleton.ca/readi/ NSERC CREATE BEST 482728-2016-CREAT, N. B., http://create-best.com/#focus The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Journal
PLOS Digital Health
DOI
10.1371/journal.pdig.0000088
Method of Research
Observational study
Subject of Research
People
Article Title
Automated step detection with 6-minute walk test smartphone sensors signals for fall risk classificiation in lower limb amputees
COI Statement
Competing interests: The authors have declared that no competing interests exist.